Traditional reverberation algorithms generally fall into two approaches: physical methods, which involve either convolving with room impulse responses (IRs) or modeling a physical space, and perceptual methods, which allow the use of practically any reverberation modules in various combinations to achieve a perceptually realistic reverberation sound. Perceptual reverberator algorithms are typically “hand tuned” where many of their parameters are found empirically. In this paper we present an automatic method of matching Feedback Delay Network parameters to real room impulse responses so that we may produce computationally efficient reverberation algorithms that perceptually match linear convolution with the target room IRs. Features are extracted from the target room IR and used to guide a Genetic Algorithm search to find the reverberator parameters.
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